The two major aims of the present study were: (i) quantify localised cortical bone adaptation at the surface level using contralateral endpoint imaging data and image analysis techniques, and (ii) investigate whether cortical bone adaptation responses are universal or region specific and dependent on the respective peak load. For this purpose, we re-analyse previously published \(\mu\)CT data of the mouse tibia loading model that investigated bone adaptation in response to sciatic neurectomy and various peak load magnitudes (F = 0, 2, 4, 6, 8, 10, 12 N). A beam theory-based approach was developed to simulate cortical bone adaptation in different sections of the tibia, using longitudinal strains as the adaptive stimuli. We developed four mechanostat models: universal, surface-based, strain directional-based, and combined surface and strain direction-based. Rates of bone adaptation in these mechanostat models were computed using an optimisation procedure (131,606 total simulations), performed on a single load case (F = 10 N). Subsequently, the models were validated against the remaining six peak loads. Our findings indicate that local bone adaptation responses are quasi-linear and bone region specific. The mechanostat model which accounted for differences in endosteal and periosteal regions and strain directions (i.e. tensile versus compressive) produced the lowest root mean squared error between simulated and experimental data for all loads, with a combined prediction accuracy of 76.6, 55.0 and 80.7% for periosteal, endosteal, and cortical thickness measurements (in the midshaft of the tibia). The largest root mean squared errors were observed in the transitional loads, i.e. F = 2 to 6 N, where inter-animal variability was highest. Finally, while endpoint imaging studies provide great insights into organ level bone adaptation responses, the between animal and loaded versus control limb variability make simulations of local surface-based adaptation responses challenging.

本研究的两个主要目标是：（i）使用对侧端点成像数据和图像分析技术量化表面水平的局部皮质骨适应，以及（ii）研究皮质骨适应反应是普遍的还是区域特异性的并依赖于各自的峰值负载。为此，我们重新分析了先前发表的小鼠胫骨负载模型的\(\mu\) CT 数据，该模型研究了坐骨神经切除术和各种峰值负载幅度（F  = 0, 2, 4, 6, 8 , 10, 12 N)。开发了一种基于梁理论的方法来模拟胫骨不同部分的皮质骨适应，使用纵向应变作为适应性刺激。我们开发了四种机械调节器模型：通用模型、基于表面的模型、基于应变方向的模型以及基于表面和应变方向的组合模型。这些机械调节器模型中的骨骼适应率是使用优化程序（总共 131,606 次模拟）计算的，并在单个负载情况下执行（F = 10 N）。随后，针对其余六个峰值负载验证了模型。我们的研究结果表明，局部骨适应反应是准线性的并且具有骨区域特异性。考虑了骨内膜和骨膜区域以及应变方向（即拉伸与压缩）差异的机械稳定器模型在所有载荷的模拟数据和实验数据之间产生了最低的均方根误差，综合预测精度为 76.6%、55.0% 和 80.7%。骨膜、骨内膜和皮质厚度测量（在胫骨中轴）。在过渡载荷中观察到最大均方根误差，即F = 2 至 6 N，其中动物间变异性最高。最后，虽然终点成像研究为器官水平骨骼适应反应提供了深入的见解，但动物和负载与控制肢体之间的变异性使得基于局部表面的适应反应的模拟具有挑战性。